# machine-learning-algorithm

**Repository Path**: zhanghy9638/machine-learning-algorithm

## Basic Information

- **Project Name**: machine-learning-algorithm
- **Description**: 记录小润了解的各种机器学习算法的实现以及基础概念，包括有监督学习，无监督学习，分类，聚类，回归；神经元模型，多层感知器，BP算法；损失函数，激活函数，梯度下降法；全连接网络、卷积神经网络、递归神经网络；训练集，测试集，交叉验证，欠拟合，过拟合；数据规范化等
- **Primary Language**: Python
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 5
- **Forks**: 3
- **Created**: 2019-05-22
- **Last Updated**: 2023-04-15

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

## Machine Learning
记录小润了解的各种机器学习算法，包括用Python的原生实现以及调用机器学习库sklearn的实现。

|名称                  |目录         |
|:--------------------|-------------|
| 线性回归 Linear Regression   | [[dir]](https://github.com/zhourunlai/machine-learning-algorithm/tree/master/logistic-regression)|
| KNN                          | [[dir]](https://github.com/zhourunlai/machine-learning-algorithm/tree/master/KNN)|
| 朴素贝叶斯 Naive Bayes       | [[dir]](https://github.com/zhourunlai/machine-learning-algorithm/tree/master/Naive-bayes)|
| 决策树 Decision Tree         | [[dir]](https://github.com/zhourunlai/machine-learning-algorithm/tree/master/decision-tree)|
| 逻辑回归 Logisitc Regression | [[dir]](https://github.com/zhourunlai/machine-learning-algorithm/tree/master/logistic-regression)|
| 支持向量机 SVM               | [[dir]](https://github.com/zhourunlai/machine-learning-algorithm/tree/master/SVM)|
| K Means                      | [[dir]](https://github.com/zhourunlai/machine-learning-algorithm/tree/master/K-Means)|

## 学习资料
* [学习资料集合](https://github.com/zhourunlai/machine-learning-algorithm/tree/master/ML%20%26%20DL)
* [《机器学习实战》](http://book.douban.com/subject/24703171/) [项目代码地址](https://github.com/zhourunlai/machine-learning-in-action)
* [《集体智慧编程》](http://book.douban.com/subject/3288908/)
* [《统计学习方法》](http://book.douban.com/subject/10590856/)
* [ coursera-ML](https://www.coursera.org/learn/machine-learning)
* [ 机器学习基石](https://www.coursera.org/course/ntumlone)
* [Microsoft: DAT208x Introduction to Python for Data Science](https://courses.edx.org/courses/course-v1:Microsoft+DAT208x+1T2016)
* [Microsoft: DAT204x Introduction to R](https://courses.edx.org/courses/course-v1:Microsoft+DAT204x+1T2016/)